Role of RXRg in NSC-derived OPCs and their differentiation
RNA-seq (gene expression) · mouse · 16 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 16 samples: 4 × WT ctrl vs 4 × Wt T3 vs 4 × RXRgKO ctrl vs 4 × RXRgKO T3Groups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE271310_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1130904 and SRA study SRP517549. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 replicated groups read from 16 sample titles; they account for 16 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8374359 WT ctrl 01 WT ctrl
- GSM8374360 WT ctrl 02 WT ctrl
- GSM8374361 WT ctrl 03 WT ctrl
- GSM8374362 WT ctrl 04 WT ctrl
- GSM8374363 Wt T3 01 Wt T3
- GSM8374364 Wt T3 02 Wt T3
- GSM8374365 Wt T3 03 Wt T3
- GSM8374366 Wt T3 04 Wt T3
- GSM8374367 RXRgKO ctrl 01 RXRgKO ctrl
- GSM8374368 RXRgKO ctrl 02 RXRgKO ctrl
- GSM8374369 RXRgKO ctrl 03 RXRgKO ctrl
- GSM8374370 RXRgKO ctrl 04 RXRgKO ctrl
- GSM8374371 RXRgKO T3 01 RXRgKO T3
- GSM8374372 RXRgKO T3 02 RXRgKO T3
- GSM8374373 RXRgKO T3 03 RXRgKO T3
- GSM8374374 RXRgKO T3 04 RXRgKO T3
No close match found for this topic, so these are simply the most-viewed datasets of the same kind.
- GSE326452 Bulk RNA-seq of mouse brain following closed head injury: role of IL-1R1 signaling 200 samples
- GSE267967 Foxp3 and BATF cooperatively direct cis-regulatory programs and gene expression for functional differentiation of Treg cells [RNA-seq] 26 samples
- GSE309993 Effector differentiation by stem-like intraepithelial γδ T cells is required for host defense against infection 25 samples
- GSE304391 Global identification of ER stress-regulated RNA binding Proteins in clonal pancreatic beta-cells, reveals an important role for DEAD-box helicase 3 X-linked (DDX3X) in the execution of the Unfolded Protein Response and the determination of cell fate. 12 samples
- GSE314817 Multi-tissue, multi-time-point transcriptomic atlas of aging in mice and rats [mouse] 2432 samples
- GSE293709 Transcriptome analysis in the prefrontal cortex of different ASD mouse models treated with drug 1565 samples
- GSE294832 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part10] 1000 samples
- GSE326100 scRNA-seq of mouse cochlea organoid cells 768 samples
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.